Open Access

Association of MHTFR Ala222Val (rs1801133) polymorphism and breast cancer susceptibility: An update meta-analysis based on 51 research studies

Diagnostic Pathology20127:171

DOI: 10.1186/1746-1596-7-171

Received: 19 November 2012

Accepted: 30 November 2012

Published: 7 December 2012

Abstract

Background

The association between MHTFR Ala222Val polymorphism and breast cancer (BC) risk are inconclusive. To derive a more precise estimation of the relationship, a systematic review and meta-analysis was performed.

Methods

A comprehensive search was conducted through researching MEDLINE, EMBASE, PubMed, Web of Science, Chinese Biomedical Literature database (CBM) and China National Knowledge Infrastructure (CNKI) databases before August 2012. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of the association.

Results

A total of 51 studies including 20,907 cases and 23,905 controls were involved in this meta-analysis. Overall, significant associations were found between MTHFR Ala222Val polymorphism and BC risk when all studies pooled into the meta-analysis (Ala/Ala vs Val/Val: OR=0.870, 95%CI=0.789–0.958,P=0.005; Ala/Val vs Val/Val: OR=0.895, 95%CI=0.821–0.976, P=0.012; dominant model: OR=0.882, 95%CI=0.808–0.963, P=0.005; and recessive model: OR = 0.944, 95%CI=0.898–0.993, P=0.026; Ala allele vs Val allele: OR = 0.935, 95%CI=0.887–0.986, P=0.013). In the subgroup analysis by ethnicity, the same results were found in Asian populations, while no significant associations were found for all comparison models in other Ethnicity populations.

Conclusion

In conclusion, our meta-analysis provides the evidence that MTHFR Ala222Val gene polymorphisms contributed to the breast cancer development.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1966146911851976

Keywords

Polymorphism Breast cancer MTFHR Ala222Val Meta-analysis

Introduction

Breast cancer is the most common cancer and the main cause of cancer mortality in women. The etiology towards to this disease is poorly understood, some risk factors including familial history of the disease, age of menarche and of menopause, diet, reproductive history, high estrogen exposure as well as genetic factors may contribute to its development[1, 2]. Studies suggest that the effect determined by low-penetrance genes, may provide a plausible explanation for BC susceptibility. Polymorphisms in genes are associated with a risk or protection against the disease. 5,10-methylenetetrahydrofolate reductase (MTHFR) is one important genes located at 1p36.3[3]. MTHFR Ala222Val polymorphism has become the most commonly studied one, which has been considered to influence the enzyme activity of MTHFR[4]. The MTHFR 222Val/Val (homozygote) genotype results in 30% enzyme activity in vitro compared with the Ala/Ala wild-type[5]. Numerous epidemiological studies have evaluated the association between the MTHFR Ala222Val polymorphisms and BC risk. However, these studies have yielded conflicting results, partially because of the possible small effect of the polymorphism on BC risk and the relatively small sample size in each of published studies. The aim of this study is to derive a more precise estimation of these associations by performing this meta-analysis.

Materials and methods

Literature search

All studies that examined the association between the MFTHR Ala222Val polymorphism and BC were identified. A comprehensive search was conducted through researching MEDLINE, EMBASE, PubMed, Web of Science, China Biomedical Literature database (CBM) and China National Knowledge Infrastructure (CNKI) databases before August 2012. The search strategy included the combination of “breast cancer,” “breast neoplasm,” “methylene-tetrahydrofolate reductase,” “MTHFR,” “Ala222Val”, “rs1801133”, “variant,” and “polymorphism.” References of the retrieved articles were also screened. Non-familial case–control studies were eligible if they determined the distribution for this polymorphism in unrelated patients with breast cancer and in a concurrent control group of healthy subjects using molecular methods for genotyping. Of the studies with the same or overlapping data by the same investigators, we selected the most recent ones with the most subjects. We evaluated all associated publications to retrieve the most eligible literatures. The reference lists of reviews and retrieved articles were hand searched at the same time. We did not include abstracts or unpublished reports. When overlapping data of the same patient population were included in more than one publication, only the most recent or complete study was used in this meta-analysis.

Inclusion and exclusion criteria

The following inclusion criteria were used to select literatures for the meta-analysis: (1) information on the evaluation of MFTHR Ala222Val polymorphism and BC susceptibility; (2)Only the cohort and case-control studies were considered;(3) sufficient genotype data were presented to calculate the OR with 95% CI. Major reasons for exclusion of studies were: (1) none-case–control studies; (2) reviews and duplication of the previous publication; (3) control population including malignant tumor patients; (4) no usable data reported.

Data extraction

Two investigators reviewed and extracted information from all eligible publications independently, according to the inclusion and exclusion criteria listed above. An agreement was reached by discussion between the two reviewers whenever there was a conflict. The following items were collected from each study: first author’s surname, year of publication, ethnicity, total number of cases and controls with Ala/Ala, Ala/Val, and Val/Val genotypes, respectively. Different descents were categorized as Caucasians, Asians, and Mixed populations which included more than one ethnic descent. For case–control studies, data were extracted separately for each group whenever possible.

Statistical analysis

The strength of the association between MFHTR Ala222Val polymorphism and BC risk was measured by ORs, whereas a sense of the precision of the estimate was given by 95% Cls. The significance of the summary OR was determined with a Z-test. We first examined MFHTR Ala222Val genotypes using co-dominant model (homogeneous co-dominant model: Ala/Ala vs Val/Val, heterogeneous co-dominant model: Ala/Val vs Val/Val), recessive (Ala/Ala vs Ala/Val + Val/Val), and dominant (Ala/Ala + Ala/Val vs Val/Val) genetic models. Then, the relationship between the allele and susceptibility to BC was examined (addictive model: Ala allele vs Val allele). Stratified analyses were also performed by ethnicities. A chi-square-based Q-statistic test and an I 2 -test test were both performed to evaluate the between-study heterogeneity of the studies.

Two models including the fixed-effects model and the random-effects model of meta-analysis were applied for dichotomous outcomes. The fixed-effects model assumes that studies are sampled from populations with the same effect size, making an adjustment to the study weights according to the in-study variance. The random-effects model assumes that studies are taken from populations with varying effect sizes, calculating the study weights both from in-study and between-study variances, considering the extent of variation, or heterogeneity. A P-value ≥0.10 for the Q-test indicated lack of heterogeneity among the studies, and so the summary OR estimate of each study was calculated by the fixed-effects modelm[6]. Otherwise, the random-effects model (DerSimonian and Laird method) was used[7]. I 2 statistic can be used to quantify heterogeneity irrespective of the number of studies. The significance of the pooled OR was determined by the Z-test and P<0.05 was considered as statistically significant. Subgroup analyses were performed by ethnicity to explore the reasons of heterogeneity. Sensitivity analyses were performed to assess the stability of the results. To investigate whether publication bias might affect the validity of the estimates, funnel plot were constructed. An asymmetric plot suggests a possible publication bias. Funnel plot asymmetry was assessed by the method of Egger’s linear regression test, a linear regression approach to measure funnel plot asymmetry on the natural logarithm scale of OR. The significance of the intercept was determined by the t-test suggested by Egger (P<0.05 was considered representative of statistically significant publication bias). All statistical tests were performed with Stata (Version 12.0, Stata Corporation, College Station, TX), using two-sided P-values.

Results

Eligible studies

51 eligible studies on MTHFR Ala222Val genotypes and colorectal cancer were identified through literature search and selection based on the inclusion and exclusion criteria [858]. The publishing year of the studies was from 2002 to 2012. There were 25 studies of Caucasian, 19 studies of Asians and 7 studies of Mixed populations. In total, 20,907 BC cases and 23,905 controls were included in the meta-analysis. The selected study characteristics were summarized in Table 1.
Table 1

The main characteristics of these studies and the distribution of MTHFR Ala222Val genotypes and alleles among cases and controls

First author [Inference]

Year

Ethnicity

 

Cases

  

Controls

 

HWE

CC

CT

TT

CC

CT

TT

Sharp[8]

2002

Caucasian

30

19

5

25

21

11

0.103

Campbell[9]

2002

Caucasian

140

162

33

118

92

23

0.420

Semenza[10]

2003

Caucasian

42

58

5

112

111

24

0.643

Langsenlehner[11]

2003

Caucasian

208

222

64

215

215

65

0.333

Ergul[12]

2003

Caucasian

60

41

17

94

87

12

0.164

Shrubsole[13]

2004

Asian

374

555

183

387

577

196

0.442

Fo¨rsti[14]

2004

Caucasian

134

81

8

181

104

13

0.689

Lee[15]

2004

Asian

58

96

32

50

80

17

0.076

Grieu[16]

2004

Caucasian

166

141

27

242

259

50

0.100

Lin[17]

2004

Asian

43

38

7

173

145

24

0.389

Qi[18]

2004

Asian

42

104

71

59

105

54

0.593

Chen[19]

2005

Mixed

398

476

189

440

509

155

0.689

Kalemi[20]

2005

Caucasian

19

16

7

23

20

8

0.313

Deligezer[21]

2005

Caucasian

98

68

23

128

83

12

0.759

Justenhoven[22]

2005

Caucasian

249

247

61

261

279

93

0.193

Chou[23]

2006

Asian

73

51

18

132

120

33

0.475

Kalyankumar[24]

2006

Caucasian

45

37

6

61

31

3

0.693

Xu[25]

2007

Mixed

398

476

189

440

509

155

0.689

Hekim[26]

2007

Caucasian

22

16

2

38

26

4

0.872

Macis[27]

2007

Caucasian

14

20

12

28

41

11

0.511

Yu[28]

2007

Asian

56

54

9

225

170

25

0.336

Reljic[29]

2007

Caucasian

40

44

9

27

34

4

0.114

Inoue[30]

2008

Asian

239

120

21

393

226

43

0.178

Kotsopoulos[31]

2008

Caucasian

383

421

140

252

341

87

0.087

Suzuki[32]

2008

Asian

150

220

84

338

425

146

0.522

Cheng[33]

2008

Asian

185

133

31

268

221

41

0.624

Langsenlehner[34]

2008

Caucasian

51

43

11

40

48

17

0.685

Ericson[35]

2009

Caucasian

255

235

50

531

452

91

0.707

Gao[36]

2009

Asian

202

305

117

235

301

88

0.592

Ma[37]

2009

Asian

124

183

81

115

188

84

0.663

Platek[38]

2009

Mixed

429

446

119

788

795

219

0.398

Henrı′quez-Herna′ndez[39]

2009

Caucasian

52

65

18

107

138

47

0.823

Cam[40]

2009

Caucasian

48

49

13

47

42

6

0.398

Maruti[41]

2009

Mixed

133

139

46

301

284

62

0.672

Ma[42]

2009

Mixed

225

188

45

222

187

49

0.309

Li[43]

2009

Asian

38

17

10

90

50

3

0.187

Yuan[44]

2009

Asian

16

35

29

32

35

13

0.516

Jin[45]

2009

Asian

18

20

3

49

41

10

0.742

Bentley[46]

2010

Caucasian

346

402

191

429

529

205

0.060

Alshatwi[47]

2010

Asian

34

50

16

36

49

15

0.800

Sangrajrang[48]

2010

Asian

410

144

9

366

110

11

0.427

Weiner[49]

2010

Caucasian

399

364

74

386

326

66

0.808

Prasad[50]

2011

Asian

124

5

1

116

8

1

0.062

Batschauer[51]

2011

Caucasian

27

34

7

42

34

9

0.593

Mohammad[52]

2011

Asian

168

53

1

198

37

0

0.190

Naushad[53]

2011

Asian

185

56

3

205

39

0

0.175

Cerne[54]

2011

Caucasian

222

238

62

108

124

37

0.882

Akram[55]

2012

Caucasian

65

25

20

55

45

10

0.855

Barbosa[56]

2012

Mixed

76

83

17

87

70

19

0.389

Lajin[57]

2012

Caucasian

44

52

23

65

48

13

0.359

Jakubowska[58]

2012

Mixed

2032

2166

580

1447

1481

422

0.156

HWE Hardy–Weinberg equilibrium.

Meta-analysis results

Overall, there was statistically significant difference in BC risk between the patients with Ala/Ala genotype and those with Val/Val genotype (OR=0.870, 95%CI=0.789-0.958, P=0.005; Figure1). Similarly, significant associations were also found in the recessive model comparison (OR=0.944, 95%CI=0.898-0.993, P=0.026; Table2) and dominant model comparison (OR=0.882, 95%CI=0.808-0.963, P=0.005; Table2). Moreover, we found significant association between Ala222Val polymorphism and BC when examining the contrast of Ala versus Val (OR=0.935, 95%CI=0.887-0.986, P=0.013; Figure2). In the stratified analysis by ethnicity, there was significant association between Ala222Val polymorphism and BC risk for Ala/Ala vs Val/Val comparison (OR=0.787, 95%CI=0.645-0.961, P=0.019; Figure3), recessive model comparison (OR=0.890, 95%CI=0.799-0.991, P=0.034; Table2), dominant model comparison (OR=0.826, 95%CI=0.703-0.972, P=0.021; Table2) and Ala allele versus Val allele comparison (OR=0.877, 95%CI=0.801-0.960, P=0.008; Figure4) among Asian populations. For Caucasian and Mixed populations, there was no significant association between Ala222Val polymorphism and breast cancer risk (Table2).
https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-7-171/MediaObjects/13000_2012_Article_659_Fig1_HTML.jpg
Figure 1

Forest plot of overall breast cancer risk associated with the MTHFR Ala222Val polymorphism (Ala/Ala versus Val/Val).

Table 2

Main results of pooled odds ratios (ORs) with confidence interval (CI) in the meta-analysis

Variables

No. of studies

 

Ala/Ala vs Val/Val

  

Ala/Ala vs Ala/Val

  

Ala/Val vs Val/Val

 

OR (95% CI)

Ph

P

OR (95% CI)

Ph

P

OR (95% CI)

Ph

P

Total

51

0.870(0.789 0.958)

0.001

0.005

0.969(0.923 1.016)

0.206

0.191

0.895(0.821 0.976)

0.021

0.012

Asian

19

0.787(0.645 0.961)

0.017

0.019

0.929(0.843 1.023)

0.212

0.132

0.865(0.753 0.993)

0.300

0.039

Caucasian

25

0.869(0.741 1.020)

0.040

0.319

1.004(0.921 1.095)

0.137

0.926

0.910(0.778 1.064)

0.031

0.238

Mixed

7

0.925(0.793 1.079)

0.050

0.087

0.958(0.898 1.022)

0.946

0.191

0.912(0.778 1.068)

0.050

0.253

Variables

No. of studies

Ala/Val + Ala/Val vs Val/Va (dominant)

Ala/Ala vs Ala/Val + Val/Va (recessive)

Ala allele vs Val allele

OR (95% CI)

P h

P

OR (95% CI)

P h

P

OR (95% CI)

P h

P

Total

51

0.882(0.808 0.963)

0.004

0.005

0.944(0.898 0.993)

0.055

0.026

0.935(0.887 0.986)

0.000

0.013

Asian

19

0.826(0.703 0.972)

0.075

0.021

0.890(0.799 0.991)

0.043

0.034

0.877(0.801 0.960)

0.003

0.008

Caucasian

25

0.916(0.790 1.063)

0.030

0.247

0.985(0.908 1.069)

0.141

0.720

0.883(0.805 0.968)

0.052

0.359

Mixed

7

0.888(0.758 1.041)

0.029

0.144

0.946(0.890 1.006)

0.773

0.076

0.957(0.838 1.094)

0.000

0.523

Ph: P value of Q-test for heterogeneity test.

https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-7-171/MediaObjects/13000_2012_Article_659_Fig2_HTML.jpg
Figure 2

Forest plot of overall breast cancer risk associated with the MTHFR Ala222Val polymorphism (Ala-allele versus Ala-allele).

https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-7-171/MediaObjects/13000_2012_Article_659_Fig3_HTML.jpg
Figure 3

Forest plot of a meta-analysis of the association between the MTHFR Ala222Val polymorphism and breast cancer susceptibility in Asians (Ala/Ala versus Val/Val).

https://static-content.springer.com/image/art%3A10.1186%2F1746-1596-7-171/MediaObjects/13000_2012_Article_659_Fig4_HTML.jpg
Figure 4

Forest plot of a meta-analysis of the association between the MTHFR Ala222Val polymorphism and breast cancer susceptibility in Asians (Ala-allele versus Ala-allele).

Sensitivity analysis

In order to compare the difference and evaluate the sensitivity of the meta-analyses, we conducted one-way sensitivity analysis to evaluate the stability of the meta-analysis. The statistical significance of the results was not altered when any single study was omitted, confirming the stability of the results. Hence, results of the sensitivity analysis suggest that the data in this meta-analysis are relatively stable and credible.

Publication bias

Begg’s funnel plot and Egger’s test were performed to assess the publication bias. The shape of funnel plots did not reveal any evidence of obvious asymmetry in all comparison models, and the Egger’s test was used to provide statistical evidence of funnel plot symmetry. The results of Begg’s test did not show any evidence of publication bias.

Discussion

Breast cancer is currently the most frequently occurring cancer and the leading causes of cancer-related death among women in the world. Single nucleotide polymorphism (SNP) is the most common form of human genetic variation, and may contribute to individual’s susceptibility to cancer, however, the underlying molecular mechanism is unknown. Previous study suggested that some variants, especially those in the promoter regions of genes, may affect either the expression or activity levels of enzymes[5961] and therefore may be mechanistically associated with cancer risk. Previous studies on the relationship between MTHFR Ala222Val polymorphisms and BC risk were contradictory. These inconsistent results are possibly because of a small effect of the polymorphism on BC risk or the relatively low statistical power of the published studies. Hence, the meta-analysis was needed to provide a quantitative approach for combining the results of various studies with the same topic, and for estimating and explaining their diversity.

Meta analysis has great power for elucidating genetic factors in cancer. On the bases of the character of cancer, the effect of one genetic component on the development of the disease can be easily masked by other genetic and environmental factors. A meta-analysis potentially investigates a large number of individuals and can estimate the effect of a genetic factor on the risk of the disease[62, 63]. The present study included data from 51 association studies that had investigated the relationship between the MTHFR Ala222Val polymorphism and BC.

This present meta-analysis, including 20,907 cases and 23,905 controls, concerned the Ala222Val polymorphism of MTHFR gene and BC risk. In the meta-analysis, we found that the variant genotypes of the MTHFR Ala222Val polymorphisms were significantly associated with BC risk. Simultaneously, the same results presented in stratified analysis by ethnicity. We found that the variant genotype of the MTHFR Ala222Val polymorphism, in Asian populations, was associated with significant increase in BC risk. Although the MTHFR Ala222Val polymorphism may be associated with DNA repair activity, no significant association of the variant genotype with BC risk was found in Caucasian and Mixed populations, suggesting the influence of the genetic variant may be masked by the presence of other as-yet unidentified causal genes involved in colorectal cancer.

Some limitations of this meta-analysis should be acknowledged. First, our result was based on unadjusted estimates, while a more precise analysis should be conducted adjusted by other factors like diet habit, smoking, drinking status, environmental factors and so on. Second, in the subgroup analyses by ethnicity, relatively limited study numbers to perform ethnic subgroup analysis of mixed populations. Moreover, there are no American and African-American descent populations. Thus, additional studies are warranted to evaluate the effect of this functional polymorphism on BC risk in different ethnicities, especially in American, African-American and Mixed populations. In addition, our analysis did not consider the possibility of gene-gene or SNP-SNP interactions or the possibility of linkage disequilibrium between polymorphisms.

Despite of some limitations, this meta-analysis provided evidence of the association between the MTHFR Ala222Val polymorphisms and BC risk, supporting the hypothesis that MTHFR Ala222Val polymorphism contributes to overall BC risk. In subgroup analysis, the same results were found in Asian populations. In order to verify our findings, well-designed studies including different ethnic groups with a careful matching between cases and controls should be considered in future association studies to confirm the results from our meta-analysis. Moreover, further evaluating the effect of gene-gene and gene-environment interactions on the Ala222Val polymorphism and BC risk are necessary.

Abbreviations

BC: 

Breast cancer

HWE: 

Hardy–Weinberg equilibrium

OR: 

Odds ratio

CI: 

Confidence interval

MTHFR: 

Methylenetetrahydrofolate reductase.

Declarations

Acknowledgements

This work was not supported by any kind of fund.

Authors’ Affiliations

(1)
Department of General Surgery, the Secondary Hospital of Tianjin Medical University

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